potential

Analyze codebase structure to identify latent capabilities and produce a cited vision portfolio.

Updated Apr 26, 2026
One-click install
npx skills add https://github.com/kennykankush/skillpack --skill potential
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: potential
Source: https://github.com/kennykankush/skillpack/tree/main/plugins/workbench/skills/potential
Command: npx skills add https://github.com/kennykankush/skillpack --skill potential

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps developers identify latent capabilities in a codebase, surface implied features, and guide ideation about future possibilities without writing code.

Core Features & Use Cases

  • Open mode: walk the building, surface visions grounded in real beams.
  • Wish mode: incorporate user wishes and evaluate them against the structure.
  • Grounding walk: consult root vision docs (VISION.md), MAP.md, and AUDIT.md for evidence.
  • Output strategy: deliver a concise portfolio with three to five visions, cited beams, and an honest assessment of feasibility and cost.

Quick Start

Ask the skill to analyze a repository and surface its latent capabilities.

Frequently Asked Questions about potential

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze a codebase to identify its latent potential and future features?

To analyze a codebase for latent potential, you can use a tool to evaluate its existing structure and root vision docs like VISION.md, MAP.md, and AUDIT.md. This process surfaces implied capabilities without writing any new code.

Can I evaluate user-proposed feature wishes against my existing codebase architecture?

Yes, you can evaluate user-proposed feature wishes against your codebase architecture using a wish mode analysis. This compares your desired features against real structural beams and delivers an honest assessment of feasibility and cost.

What is the best way to surface architectural visions grounded in existing code flows?

The best way to surface architectural visions grounded in code flows is an open mode analysis. It walks the building blocks of your repository and outputs a portfolio of three to five visions backed by cited files.

Does codebase potential analysis work for repositories of varying sizes?

Yes, codebase potential analysis works for repositories of varying sizes. It scales to evaluate the structure of different codebases, reading root vision docs if present to ground the architectural assessment.

How do I generate a portfolio of future development visions for my repository?

You generate a portfolio of future development visions by analyzing existing repository beams and consulting vision docs. This delivers a compact portfolio containing three to five visions with cited evidence references.